Considering that the prediction uncertainty of object boundaries is higher than that of the center of an object [1]}, we use the following two steps in the flood-fill.
The first step is an erosion that removes pixels where the neighbors within a kernel of size \(d\)  show at least one different semantic label resulting in the eroded mask \(\mathcal {S}_{\mathrm {raw}}^{\mathrm {eroded}}\) .
Combining this mask with the depth information generated from the vertex map \(\mathcal {V}_D\) , we then fill-in the eroded mask.
To this end, we set the label of an empty boundary pixel to the neighboring labeled pixels if the distances of the corresponding points are consistent, i.e., less than a threshold \(\theta \) .
